Thermo-Viscoelastic Response of 3D Braided Composites Based on a Novel FsMsFE Method

Theoretical Analysis of Thermophysical Properties of 3D Carbon/Epoxy Braided Composites with Varying Temperature

A three-dimensional helix geometry unit cell is established to simulate the complex spatial configuration of 3D braided composites. Initially, different types of yarn factors, such as yarn path, cross-sectional shape, properties, and braid direction, are explained. Then, the multiphase finite element method is used to develop a new theoretical calculation procedure based on the unit cell for predicting the impacts of environmental temperature on the thermophysical properties of 3D four-direction carbon/epoxy braided composites. The changing rule and distribution characteristics of the thermophysical properties for 3D four-direction carbon/epoxy braided composites are obtained at temperatures ranging from room temperature to 200 °C. The influences of environmental temperature on the coefficients of thermal expansion (CTE) and the coefficients of thermal conduction (CTC) are evaluated, by which some important conclusions are drawn. A comparison is conducted between theoretical and experimental results, revealing that variations in temperature exert a notable influence on the thermophysical characteristics of 3D four-directional carbon/epoxy braided composites. The theoretical calculation procedure is an effective tool for the mechanical property analysis of composite materials with complex geometries.

Damage Monitoring of Braided Composites Using CNT Yarn Sensor Based on Artificial Fish Swarm Algorithm

This study aims to enable intelligent structural health monitoring of internal damage in aerospace structural components, providing a crucial means of assuring safety and reliability in the aerospace field. To address the limitations and assumptions of traditional monitoring methods, carbon nanotube (CNT) yarn sensors are used as key elements. These sensors are woven with carbon fiber yarns using a three-dimensional six-way braiding process and cured with resin composites. To optimize the sensor configuration, an artificial fish swarm algorithm (AFSA) is introduced, simulating the foraging behavior of fish to determine the best position and number of CNT yarn sensors. Experimental simulations are conducted on 3D braided composites of varying sizes, including penetration hole damage, line damage, and folded wire-mounted damage, to analyze the changes in the resistance data of carbon nanosensors within the damaged material. The results demonstrate that the optimized configuration of CNT yarn sensors based on AFSA is suitable for damage monitoring in 3D woven composites. The experimental positioning errors range from 0.224 to 0.510 mm, with all error values being less than 1 mm, thus achieving minimum sensor coverage for a maximum area. This result not only effectively reduces the cost of the monitoring system, but also improves the accuracy and reliability of the monitoring process.